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BackgroundThe skin fungal communities of animals play a crucial role in maintaining host health and defending against pathogens. Because fungal infections can affect the skin microbiota of bats, gaining a comprehensive understanding of the characteristics of healthy bat skin fungal communities and the ecological processes driving them provides valuable insights into the interactions between pathogens and fungi.MethodsWe used Kruskal–Wallis tests and Permutational Multivariate Analysis of Variance (PERMANOVA) to clarify differences in skin fungal community structure among bat species. A Generalized Linear Model (GLM) based on a quasi-Poisson distribution and partial distance-based redundancy analysis (db-RDA) was performed to assess the influence of variables on skin fungal communities. Using community construction models to explore the ecological processes driving fungal community changes, t-tests and Wilcoxon tests were used to compare the alpha diversity and species abundance differences between the fungal structure on bat species’ skin and the environmental fungal pool.ResultsWe found significant differences in the composition and diversity of skin fungal communities among bat species influenced by temperature, sampling site, and body mass index. Trophic modes and skin fungal community complexity also varied among bat species. Null model and neutral model analysis demonstrated that deterministic processes dominated the assembly of skin fungal communities, with homogeneous selection as the predominant process. Skin fungal communities on bat species were impacted by the environmental fungal reservoir, and actively selected certain amplicon sequence variants (ASVs) from the environmental reservoir to adhere to the skin.ConclusionIn this study, we revealed the structure and the ecological process driving the skin fungal community across bat species in northern China. Overall, these results broaden our knowledge of skin fungal communities among bat species, which may be beneficial to potential strategies for the protection of bats in China.

Abstract Background The majority of bat species have developed remarkable echolocation ability, especially for the laryngeally echolocating bats along with high-frequency hearing. Adaptive evolution has been widely detected for the cochleae in the laryngeally echolocating bats, however, limited understanding for the brain which is the central to echolocation signal processing in the auditory perception system, the laryngeally echolocating bats brain may also undergo adaptive changes. Result In order to uncover the molecular adaptations related with high-frequency hearing in the brain of laryngeally echolocating bats, the genes expressed in the brain of Rhinolophus ferrumequinum (CF bat) and Myotis pilosus (FM bat) were both detected and also compared. A total of 346,891 genes were detected and the signal transduction mechanisms were annotated by the most abundant genes, followed by the transcription. In hence, there were 3,088 DEGs were found between the two bat brains, with 1,426 highly expressed in the brain of R. ferrumequinum, which were significantly enriched in the neuron and neurodevelopmental processes. Moreover, we found a key candidate hearing gene, ADCY1, playing an important role in the R. ferrumequinum brain and undergoing adaptive evolution in CF bats. Conclusions Our study provides a new insight to the molecular bases of high-frequency hearing in two laryngeally echolocating bats brain and revealed different nervous system activities during auditory perception in the brain of CF bats.

ABSTRACTThe gut microbiome is a symbiotic microbial community associated with the host and plays multiple important roles in host physiology, nutrition, and health. A number of factors have been shown to influence the gut microbiome, among which diet is considered to be one of the most important; however, the relationship between diet composition and gut microbiota in wild mammals is still not well recognized. Herein, we characterized the gut microbiota of bats and examined the effects of diet, host taxa, body size, gender, elevation, and latitude on the gut microbiota. The cytochrome C oxidase subunit I (COI) gene and 16S rRNA gene amplicons were sequenced from the feces of eight insectivorous bat species in southern China, including Miniopterus fuliginosus, Aselliscus stoliczkanus, Myotis laniger, Rhinolophus episcopus, Rhinolophus osgoodi, Rhinolophus ferrumequinum, Rhinolophus affinis, and Rhinolophus pusillus. The results showed that the composition of gut microbiome and diet exhibited significant differences among bat species. Diet composition and gut microbiota were significantly correlated at the order, family, genus, and operational taxonomic unit levels, while certain insects had a marked effect on the gut microbiome at specific taxonomic levels. In addition, elevation, latitude, body weight of bats, and host species had significant effects on the gut microbiome, but phylosymbiosis between host phylogeny and gut microbiome was lacking. These findings clarify the relationship between gut microbiome and diet and contribute to improving our understanding of host ecology and the evolution of the gut microbiome in wild mammals.IMPORTANCEThe gut microbiome is critical for the adaptation of wildlife to the dynamic environment. Bats are the second-largest group of mammals with short intestinal tract, yet their gut microbiome is still poorly studied. Herein, we explored the relationships between gut microbiome and food composition, host taxa, body size, gender, elevation, and latitude. We found a significant association between diet composition and gut microbiome in insectivorous bats, with certain insect species having major impacts on gut microbiome. Factors like species taxa, body weight, elevation, and latitude also affected the gut microbiome, but we failed to detect phylosymbiosis between the host phylogeny and the gut microbiome. Overall, our study presents novel insights into how multiple factors shape the bat’s gut microbiome together and provides a study case on host-microbe interactions in wildlife.

Abstract Mapping tumor metabolic remodeling and their spatial crosstalk with surrounding non-tumor cells can fundamentally improve our understanding of tumor biology, facilitates the designing of advanced therapeutic strategies. Here, we present an integration of mass spectrometry imaging-based spatial metabolomics and lipidomics with microarray-based spatial transcriptomics to hierarchically visualize the intratumor metabolic heterogeneity and cell metabolic interactions in same gastric cancer sample. Tumor-associated metabolic reprogramming is imaged at metabolic-transcriptional levels, and maker metabolites, lipids, genes are connected in metabolic pathways and colocalized in the heterogeneous cancer tissues. Integrated data from spatial multi-omics approaches coherently identify cell types and distributions within the complex tumor microenvironment, and an immune cell-dominated “tumor-normal interface” region where tumor cells contact adjacent tissues are characterized with distinct transcriptional signatures and significant immunometabolic alterations. Our approach for mapping tissue molecular architecture provides highly integrated picture of intratumor heterogeneity, and transform the understanding of cancer metabolism at systemic level.

The herbicide paraquat is an agonist of Stromal Interaction Molecule 1 (STIM1), leading to extracellular calcium entry observed in epithelial-mesenchymal transition in alveolar cells during pulmonary fibrosis.

Understanding trophic niche differentiation is critical for exploring interspecific competition and stable coexistence among morphologically similar sympatric species. Bats are an ideal model for studying trophic niche differentiation among species because of their high taxonomic and ecological diversities, as well as their special life history traits. Although many factors can affect bat trophic niches, few studies have combined multiple factors to investigate the influences on bat trophic niches. In this study, we analyzed the summer diet and potential influencing factors of five sympatric rhinolophid bats in southwestern China: Rhinolophus macrotis, Rhinolophus osgoodi, Rhinolophus ferrumequinum, Rhinolophus affinis, and Rhinolophus pusillus. All five species mainly fed on Lepidopteran and Dipteran insects, with a large trophic niche breadth for each species and a low degree of dietary overlap. With the exception of R. affinis and R. pusillus, significant differences in diet composition were detected among species, which indicated relatively low interspecific competition. Canonical correspondence analysis showed that both echolocation calls and body size significantly affected interspecific diet differentiation, while wing morphology and bite force had relatively weak effects. This study suggests that the combined effects of multiple factors may drive trophic niche differentiation among five rhinolophid bat species in the study area.

Abstract Background The mechanisms of Gastric cancer (GC) initiation and progression are complicated, at least partly owing to the dynamic changes of gene regulation during carcinogenesis. Thus, investigations on the changes in regulatory networks can improve the understanding of cancer development and provide novel insights into the molecular mechanisms of cancer. Methods Differential co-expression analysis (DCEA), differential gene regulation network (GRN) modeling and differential regulation analysis (DRA) were integrated to detect differential transcriptional regulation events between gastric normal mucosa and cancer samples based on GSE54129 dataset. Cytological experiments and IHC staining assays were used to validate the dynamic changes of CREB1 regulated targets in different stages. Results A total of 1955 differentially regulated genes (DRGs) were identified and prioritized in a quantitative way. Among the top 1% DRGs, 14 out of 19 genes have been reported to be GC relevant. The four transcription factors (TFs) among the top 1% DRGs, including CREB1, BPTF, GATA6 and CEBPA, were regarded as crucial TFs relevant to GC progression. The differentially regulated links (DRLs) around the four crucial TFs were then prioritized to generate testable hypotheses on the differential regulation mechanisms of gastric carcinogenesis. To validate the dynamic alterations of gene regulation patterns of crucial TFs during GC progression, we took CREB1 as an example to screen its differentially regulated targets by using cytological and IHC staining assays. Eventually, TCEAL2 and MBNL1 were proved to be differentially regulated by CREB1 during tumorigenesis of gastric cancer. Conclusions By combining differential networking information and molecular cell experiments verification, testable hypotheses on the regulation mechanisms of GC around the core TFs and their top ranked DRLs were generated. Since TCEAL2 and MBNL1 have been reported to be potential therapeutic targets in SCLC and breast cancer respectively, their translation values in GC are worthy of further investigation.

Summary White‐nose syndrome, a disease that is caused by the psychrophilic fungus Pseudogymnoascus destructans, has threatened several North America bat species with extinction. Recent studies have shown that East Asian bats are infected with P. destructans but show greatly reduced infections. While several factors have been found to contribute to these reduced infections, the role of specific microbes in limiting P. destructans growth remains unexplored. We isolated three bacterial strains with the ability to inhibit P. destructans, namely, Pseudomonas yamanorum GZD14026, Pseudomonas brenneri XRD11711 and Pseudomonas fragi GZD14479, from bats in China. Pseudomonas yamanorum, with the highest inhibition score, was selected to extract antifungal active substance. Combining mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy analyses, we identified the active compound inhibiting P. destructans as phenazine‐1‐carboxylic acid (PCA), and the minimal inhibitory concentration (MIC) was 50.12 μg ml−1. Whole genome sequencing also revealed the existence of PCA biosynthesis gene clusters. Gas chromatography‐mass spectrometry (GC‐MS) analysis identified volatile organic compounds. The results indicated that 10 ppm octanoic acid, 100 ppm 3‐tert‐butyl‐4‐hydroxyanisole (isoprenol) and 100 ppm 3‐methyl‐3‐buten‐1‐ol (BHA) inhibited the growth of P. destructans. These results support that bacteria may play a role in limiting the growth of P. destructans on bats.

Abstract Background The American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen) presented technical standards for interpretation and reporting of constitutional copy-number variants in 2019 (the standards). Although ClinGen developed a web-based CNV classification calculator based on scoring metrics, it can only track and tally points that have been assigned based on observed evidence. Here, we developed AutoCNV (a semiautomatic automated CNV interpretation system) based on the standards, which can automatically generate predictions on 18 and 16 criteria for copy number loss and gain, respectively. Results We assessed the performance of AutoCNV using 72 CNVs evaluated by external independent reviewers and 20 illustrative case examples. Using AutoCNV, it showed that 100 % (72/72) and 95 % (19/20) of CNVs were consistent with the reviewers’ and ClinGen-verified classifications, respectively. AutoCNV only required an average of less than 5 milliseconds to obtain the result for one CNV with automated scoring. We also applied AutoCNV for the interpretation of CNVs from the ClinVar database and the dbVar database. We also developed a web-based version of AutoCNV (wAutoCNV). Conclusions AutoCNV may serve to assist users in conducting in-depth CNV interpretation, to accelerate and facilitate the interpretation process of CNVs and to improve the consistency and reliability of CNV interpretation.

Increasing evidence has elucidated that the tumor microenvironment (TME) shows a strong association with tumor progression and therapeutic outcome. We comprehensively estimated the TME infiltration patterns of 111 gastric cancer (GC) and 21 normal stomach mucosa samples based on bulk transcriptomic profiles based on which GC could be clustered as three subtypes, TME-Stromal, TME-Mix, and TME-Immune. The expression data of TME-relevant genes were utilized to build a GC prognostic model—GC_Score. Among the three GC TME subtypes, TME-Stomal displayed the worst prognosis and the highest GC_Score, while TME-Immune had the best prognosis and the lowest GC_Score. Connective tissue growth factor (CTGF), the highest weighted gene in the GC_Score, was found to be overexpressed in GC. In addition, CTGF exhibited a significant correlation with the abundance of fibroblasts. CTGF has the potential to induce transdifferentiation of peritumoral fibroblasts (PTFs) to cancer-associated fibroblasts (CAFs). Beyond characterizing TME subtypes associated with clinical outcomes, we correlated TME infiltration to molecular features and explored their functional relevance, which helps to get a better understanding of carcinogenesis and therapeutic response and provide novel strategies for tumor treatments.

BackgroundThe tumor microenvironment (TME), which involves infiltration of multiple immune cells into the tumor tissues, plays an essential role in clinical benefit to therapy. The chemokines and their receptors influence migration and functions of both tumor and immune cells. Also, molecular characteristics are associated with the efficacy of melanoma therapy. However, there lacked exploration of immune characteristics and the association with molecular characteristics.MethodsWe collected the currently available 569 melanoma samples that had both the genomic and transcriptional data from TCGA and SRA databases. We first identified TME subtypes based on the developed immune signatures, and then divided the samples into two immune cohorts based on the immune score. Next, we estimated the compositions of the immune cells of the two cohorts, and performed differential expression genes (DEGs) and functional enrichments. In addition, we investigated the interactions of chemokines and their receptors under immune cells. Finally, we explored the genomic characteristics under different immune subtypes.ResultsTME type D had a better prognosis among the four subtypes. The high-immunity cohort had significantly high 16 immune cells. The 63 upregulated and 384 downregulated genes in the high-immunity cohort were enriched in immune-related biological processes, and keratin, pigmentation and epithelial cells, respectively. The correlations of chemokines and their receptors with immune cell infiltration, such as CCR5-CCL4/CCL5 and CXCR3-CXCL9/CXCL10/CXCL11/CXCL13 axis, showed that the recruitments of 11 immune cells, such as CD4T cells and CD8T cells, were modulated by chemokines and their receptors. The proportions of the four TME subtypes in each molecular subtype were comparable. The two driver genes, CDKN2A and PRB2, had significantly different MAFs between the high-immunity and low-immunity.ConclusionWe dissected the characteristics of immune infiltration, the interactions of chemokines and their receptors under immune cells, and the correlation of molecular and immune characteristics. Our work will enable the reasonable selection of anti-melanoma treatments and accelerate the development of new therapeutic strategies for melanoma.

Host-associated skin bacteria are essential for resisting pathogen infections and maintaining health. However, we have little understanding of how chiropteran skin microbiota are distributed among bat species and their habitats, or of their putative roles in defending against Pseudogymnoascus destructans in China. In this study, we characterized the skin microbiomes of four bat species at five localities using 16S rRNA gene amplicon sequencing to understand their skin microbial composition, structure, and putative relationship with disease. The alpha- and beta-diversities of skin microbiota differed significantly among the bat species, and the differences were affected by environmental temperature, sampling sites, and host body condition. The chiropteran skin microbial communities were enriched in bacterial taxa that had low relative abundances in the environment. Most of the potential functions of skin microbiota in bat species were associated with metabolism. Focusing on their functions of defense against pathogens, we found that skin microbiota could metabolize a variety of active substances that could be potentially used to fight P. destructans. The skin microbial communities of bats in China are related to the environment and the bat host, and may be involved in the host’s defense against pathogens.

The current methods for evaluating the operating condition of electricity transmission lines (ETLs) and providing early warning have several problems, such as the low correlation of data, ignoring the influence of seasonal factors, and strong subjectivity. This paper analyses the sensitive factors that influence dynamic key evaluation indices such as grounding resistance, sag, and wire corrosion, establishes the evaluation criteria of the ETL operation state, and proposes five ETL status levels and seven principles for selecting evaluation indices. Nine grade I evaluation indices and twenty-nine grade II evaluation indices, including passageway and meteorological environments, are determined. The cloud model theory is embedded and used to propose a warning technology for the operation state of ETLs based on inspection defect parameters and the cloud model. Combined with the inspection defect parameters of a line in the Baicheng district of Jilin Province and the critical evaluation index data such as grounding resistance, sag, and wire corrosion, which are used to calculate the timeliness of the data, the solid line is evaluated. The research shows that the dynamic evaluation model is correct and that the ETL status evaluation and early warning method have reasonable practicability.

Rickett’s big-footed bat, Myotis pilosus, which belongs to the family Vespertilionida, is the only known piscivorous bat in East Asia. Accurate whole genome and transcriptome annotations are essential for the study of bat biological evolution. The lack of a whole genome for M. pilosus has limited our understanding of the molecular mechanisms underlying the species’ evolution, echolocation, and immune response. In the present work, we sequenced the entire transcriptome using error-corrected PacBio single-molecule real-time (SMRT) data. Then, a total of 40 GB of subreads were generated, including 29,991 full-length non-chimeric (FLNC) sequences. After correction by Illumina short reads and de-redundancy, we obtained 26,717 error-corrected isoforms with an average length of 3018.91 bp and an N50 length of 3447 bp. A total of 1528 alternative splicing (AS) events were detected by transcriptome structural analysis. Furthermore, 1032 putative transcription factors (TFs) were identified, with additional identification of several long non-coding RNAs (lncRNAs) with high confidence. Moreover, several key genes, including PRL-2, DPP4, Glul, and ND1 were also identified as being associated with metabolism, immunity, nervous system processes, and auditory perception. A multitude of pattern recognition receptors was identified, including NLR, RLR, SRCR, the antiviral molecule IRF3, and the IFN receptor subunit IFNAR1. High-quality reference genomes at the transcriptome level may be used to quantify gene or transcript expression, evaluate alternative splicing levels, identify novel transcripts, and enhance genome annotation in bats.

In the process of species differentiation and adaption, the relative influence of natural selection on gene expression variation often remains unclear (especially its impact on phenotypic divergence). In this study, we used differentially expressed genes from brain, cochlea, and liver samples collected from two species of bats to determine the gene expression variation forced by natural selection when comparing at the interspecific (Rhinolophus siamensis and R. episcopus episcopus) and the intraspecific (R. e. episcopus and R. episcopus spp.) levels. In both cases, gene expression variation was extensively adaptive (>66.0%) and mainly governed by directional selection, followed by stabilizing selection, and finally balancing selection. The expression variation related to acoustic signals (resting frequency, RF) and body size (forearm length, FA) was also widely governed by natural selection (>69.1%). Different functional patterns of RF- or FA-related adaptive expression variation were found between the two comparisons, which manifested as abundant immune-related regulations between subspecies (indicating a relationship between immune response and phenotypic adaption). Our study verifies the extensive adaptive expression variation between both species and subspecies and provides insight into the effects of natural selection on species differentiation and adaptation as well as phenotypic divergence at the expression level.

Background: Due to the molecular mechanism complexity and heterogeneity of gastric cancer (GC), mechanistically interpretable biomarkers were required for predicting prognosis and discovering therapeutic targets for GC patients. Methods: Based on a total of 824 GC-specific fitness genes from the Project Score database, LASSOCox regression was performed in TCGA-STAD cohort to construct a GC Prognostic (GCP) model which was then evaluated on 7 independent GC datasets. Targets prioritization was performed in GC organoids. ARGLU1 was selected to further explore the biological function and molecular mechanism. We evaluated the potential of ARGLU1 serving as a promising therapeutic target for GC using patients derived xenograft (PDX) model. Findings: The 9-gene GCP model showed a statistically significant prognostic performance for GC patients in 7 validation cohorts. Perturbation of SSX4, DDX24, ARGLU1 and TTF2 inhibited GC organoids tumor growth. The results of tissue microarray indicated lower expression of ARGLU1 was correlated with advanced TNM stage and worse overall survival. Over-expression ARGLU1 significantly inhibited GC cells viability in vitro and in vivo. ARGLU1 could enhance the transcriptional level of mismatch repair genes including MLH3, MSH2, MSH3 and MSH6 by potentiating the recruitment of SP1 and YY1 on their promoters. Moreover, inducing ARGLU1 by LNP-formulated saRNA significantly inhibited tumor growth in PDX model. Interpretation: Based on genome-wide functional screening data, we constructed a 9-gene GCP model with satisfactory predictive accuracy and mechanistic interpretability. Out of nine prognostic genes, ARGLU1 was verified to be a potential therapeutic target for GC. Funding: National Natural Science Foundation of China.

Abstract Background Although the sensory drive hypothesis can explain the geographic variation in echolocation frequencies of some bat species, the molecular mechanisms underlying this phenomenon are still unclear. The three lineages of greater horseshoe bat (Rhinolophus ferrumequinum) in China (northeast, central-east, and southwest) have significant geographic variation in resting frequencies (RF) of echolocation calls. Because their cochleae have an acoustic fovea that is highly sensitive to a narrow range of frequencies, we reported the transcriptomes of cochleae collected from three genetic lineages of R. ferrumequinum, which is an ideal organism for studying geographic variation in echolocation signals, and tried to understand the mechanisms behind this bat phenomenon by analyzing gene expression and sequence variation. Results A total of 8190 differentially expressed genes (DEGs) were identified. We identified five modules from all DEGs that were significantly related to RF or forearm length (FL). DEGs in the RF-related modules were significantly enriched in the gene categories involved in neural activity, learning, and response to sound. DEGs in the FL-related modules were significantly enriched in the pathways related to muscle and actin functions. Using 21,945 single nucleotide polymorphisms, we identified 18 candidate unigenes associated with hearing, five of which were differentially expressed among the three populations. Additionally, the gene ERBB4, which regulates diverse cellular processes in the inner ear such as cell proliferation and differentiation, was in the largest module. We also found 49 unigenes that were under positive selection from 4105 one-to-one orthologous gene pairs between the three R. ferrumequinum lineages and three other Chiroptera species. Conclusions The variability of gene expression and sequence divergence at the molecular level might provide evidence that can help elucidate the genetic basis of geographic variation in echolocation signals of greater horseshoe bats.

Abstract Applications of graphene as transparent conductive electrodes (TCE) have been hindered either by high cost of single crystal graphene or balance between transparency and sheet resistance of polycrystalline graphene. In this work, we propose to fabricate multilayer graphene film grids (MGFG) to enhance transparency and keep low sheet resistance through IR laser tailoring. It is proved that the transparency of MGFG could be increased by 200 times while remaining its competitive sheet resistance as low as 340 Ω sq−1 through adjusting the tailoring grid, and the corresponding figures of merit (FoM) is increased from 0.1 to 3.6. As-obtained MGFG is demonstrated in generating controllable local thermal field and defogging efficiently. The strategy of laser-tailoring grid will greatly advance the applications of graphene for transparent electrodes in industry.

Abstract Background One of the key reasons for the high failure rate of new agents and low therapeutic benefit of approved treatments is the lack of preclinical models that mirror the biology of human tumors. At present, the optimal cancer model for drug response study to date is patient-derived xenograft (PDX) models. PDX recaptures both inter- and intra-tumor heterogeneity inherent in human cancer, which represent a valuable platform for preclinical drug testing and personalized medicine applications. Building efficient drug response analysis tools is critical but far from adequate for the PDX platform. Results In this work, we first classified the emerging PDX preclinical trial designs into four patterns based on the number of tumors, arms, and animal repeats in every arm. Then we developed an R package, DRAP, which implements Drug Response Analyses on PDX platform separately for the four patterns, involving data visualization, data analysis and conclusion presentation. The data analysis module offers statistical analysis methods to assess difference of tumor volume between arms, tumor growth inhibition (TGI) rate calculation to quantify drug response, and drug response level analysis to label the drug response at animal level. In the end, we applied DRAP in two case studies through which the functions and usage of DRAP were illustrated. Conclusion DRAP is the first integrated toolbox for drug response analysis and visualization tailored for PDX platform. It would greatly promote the application of PDXs in drug development and personalized cancer treatments.

Digestive cancers-including gastric cancer (GC), colorectal cancer, hepatocellular carcinoma, esophageal cancer, and pancreatic cancer-accounted for 26% of cancer cases and 35% of cancer deaths worldwide in 2018. It is crucial and urgent to develop biomarkers for the diagnosis, prognosis, and therapeutic benefits of digestive cancers, especially for GC, since the incidence of GC is lower only than lung cancer in China, is hard to detect at an early stage, and is associated with poor prognosis. Mucins, glycoproteins encoded by MUC family genes, act as a part of a physical barrier in the digestive tract and participate in various signaling pathways. Some mucins have been used or proposed as biomarkers for carcinomas, such as MUC16 (CA125) and MUC4. However, there are no systematic investigations on the association of MUC family members with diagnoses and clinical outcomes even though relevant data have been largely accumulated in the past decade. By analyzing transcriptomic and clinical data of digestive cancer samples from TCGA involving colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), liver hepatocellular carcinoma (LIHC), stomach adenocarcinoma (STAD), and pancreatic adenocarcinoma (PAAD), it was found that expressions levels of MUC15, MUC13, and MUC21 were individually associated with survival for digestive cancers, and high expressions of EMCN (MUC14) and MUC15 were correlated with poor survival for STAD. Cox regression analysis indicated the predictive power of an EMCN/MUC15 combination for overall survival (OS) of GC patients, which was validated on an independent dataset from GEO. EMCN/MUC15 correlated genes were identified to be enriched in cancer-related processes, such as vasculature development, mitosis, and immunity. Therefore, we propose that an EMCN/MUC15 combination could be a potential prognostic signature for gastric cancer.

Abstract Lethal ventricular tachyarrhythmia (LVTA) is the most prevalent electrophysiological underpinning of sudden cardiac death (SCD), a condition that occurs in response to multiple pathophysiological abnormalities. The aim of this study was to identify common lipid features of LVTA that were induced by distinct pathophysiological conditions, thereby facilitating the discovery of novel SCD therapeutic targets. Two rat LVTA-SCD models were established to mimic myocardial infarction (MI) and myocardial ion channel diseases. Myocardial and serum specimens were analyzed using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS)-based lipidomics. The lipid profiles of the myocardial and serum specimens were similar between the models. Eleven myocardial lipid classes were altered, including downregulations of: cardiolipin, ceramide, phosphatidylinositol, phosphatidylethanolamine, triacylglycerol, diacylglycerol, phosphatidylglycerol, lysophosphatidylethanolamine and phosphatidylserine, and upregulations of: lysophosphatidylcholine and phosphatidic acid. Serum concentrations of triacylglycerol, lysophosphatidylcholine, phosphatidylethanolamine and phosphatidylinositol were also altered. Alterations of lipids in paired myocardia and sera were closely correlated. Cardiolipin 70:5, cardiolipin 74:9 and ceramide d34:2 were tested as potential biomarkers of LVTA. The results indicate that there are common LVTA lipid profiles induced by MI and myocardial ion channel diseases, potentially offering novel LVTA-SCD therapeutic targets.

In order to reduce the influence of surface burns and other defects in the processing of pure iron parts for a functional properties test, and to improve the accuracy and usability of the test results, abrasive belt grinding is used for surface grinding. Because of the long circumference of the belt, and the long cooling time of the abrasive particles, cold grinding can be achieved, so that the incidence of surface burns, machining hardening, and other defects can be reduced. An experimental platform for belt grinding of pure iron parts for a functional properties test was built, and corresponding belt grinding experiments were carried out. The influences of grinding parameters, such as belt velocity, feed velocity, the grinding track on the microcosmic morphology, surface roughness, surface residual stress, and micro-hardness were studied. The results showed that belt grinding improved the surface integrity, the surface roughness was less than Ra 0.4 μm, the surface residual stress ranged from −253.84 MPa to −164.14 MPa, and the micro-hardness ranged from 118 HV to 170 HV. Furthermore, to get the workpiece surface to mostly suit the functional performance test, a high abrasive belt linear speed, a low grinding depth, and a feed speed should be selected, and the processing should be conducted with a circular trajectory.

Many template-based modeling (TBM) methods have been developed over the recent years that allow for protein structure prediction and for the study of structure-function relationships for proteins. One major problem all TBM algorithms face, however, is their unsatisfactory performance when proteins under consideration are low-homology. To improve the performance of TBM methods for such targets, a novel model evaluation method was developed here, and named MEFTop. Our novel method focuses on evaluating the topology by using two novel groups of features. These novel features included secondary structure element (SSE) contact information and 3-dimensional topology information. By combining MEFTop algorithm with FR-t5, a threading program developed by our group, we found that this modified TBM program, which was named FR-t5-M, exhibited significant improvements in predictive abilities for low-homology protein targets. We further showed that the MEFTop could be a generalized method to improve threading programs for low-homology protein targets. The softwares (FR-t5-M and MEFTop) are available to non-commercial users at our website: http://jianglab.ibp.ac.cn/lims/FRt5M/FRt5M.html.